Abstract

Despite the high demand for goat meat, the quantity of meat that is produced
from the indigenous goats is low and insufficient to meet the demand. This
is due to their small body size and inherent low genetic potential for
growth coupled with poor management especially feeding. Improvement of goat
productivity through selection takes long time to achieve and may be
difficult for some traits. Information on polymorphisms in candidate genes
for growth including myostatin gene could be used with pedigree information
in marker assisted selection to get high genetic response more quickly. This
study assessed polymorphisms of the intron 2 and exon 3 of the myostatin
gene in Pare, Sonjo, Blended and Boer goats.

Only one singleton polymorphic
site T298C was detected in the Boer goat population and all other goats were
monomorphic. Two alleles, T and C were detected in Boer goats with
frequencies of 0.98 and 0.02, respectively, and two genotypes TT and TC with
frequency of 0.97 and 0.03, respectively. Allele T was fixed in the Blended,
Pare and Sonjo populations. Blended goats were heavier at all stages of
growth than Pare and Sonjo goats. However, due to lack of polymorphism in
the three goat populations the association between the alleles of the
myostatin gene and growth performance could not be confirmed. It can be
concluded that there are variation in growth performance among the Blended,
Pare and Sonjo goats but the variation could not be associated with the
myostatin gene. Other genes for growth could be responsible for the observed
variation.

Key words: growth, local goats, myostatin, strain

Introduction

Goats play an important role in the livelihoods and income generation of
smallholder farmers in rural areas of Tanzania. The goats are mainly kept
for meat production their meat is rank second to beef in terms of sales and
consumption (Chenyambuga et al 2004). Goat meat in Tanzania is
predominantly produced from the Small East African (SEA) goats which are
raised in all ecological zones of the country. Other breeds that are used,
though to a lesser extent alongside the SEA goats for meat production are
the Boer and Blended goats. Pare and Sonjo goats belong to the Small East
African goat breed which is well adapted and widely distributed in almost
all ecological zones where they are used for meat production. Blended goats
are the result of three-way crosses (55% Kamorai, 30% Boer and 15%
indigenous), developed at Malya, Tanzania, which were stabilised in the late
1960s (Das 1989). They are dual purpose goats but are mainly kept for meat
production because of their relatively higher growth rate and bigger mature
size compared to the SEA goat strains (Das 1989). Since their development
in the 1960s, Blended goats have been maintained mostly in Government farms
and research stations where they are multiplied and distributed to farmers.
The Boer goat is a meat purpose breed intensively selected for rapid growth
(Malan 2000) and therefore, widely used in crossbreeding to improve goat
productivity in different parts of the world. Despite the high growth
advantage of the Blended goats and the excellent adaptation to the local
conditions of the SEA goat strains, improvement through within breed
selection has not been practised.

The demand for goat meat in urban areas has increased recently due to growth
of tourism, expanding mining industries and establishment of international
hotels in Tanzania (Kinunda-Rutashobya, 2003). Despite the high demand for
goat meat, the biggest challenge remains with the quantity of meat that is
produced from these animals. This is due to small body size and inherent low
genetic potential for growth coupled with poor management especially
feeding. Efforts to improve productivity of goats in Tanzania, like
elsewhere in developing countries have always focused on crossbreeding
rather than selection within the local stock. Selection for production
traits has been practiced mostly in intensive production systems,
essentially based on dairy recording schemes combined with artificial
insemination (Montaldo and Manfredi 2002). In most developing countries,
Tanzania included, goat breeding programs for local breeds under extensive
systems are not common due to difficulties of setting up such a program in
the marginal areas where goats are often raised (Lôbo et al.,
2010). Nevertheless, genetic improvement of locally adapted breeds is
important to realizing sustainable production systems.

DNA technologies can be used to reliably realize intense and accurate
selection and short generation intervals and to enable genetic improvement
of locally adapted breeds to contribute to the required livestock
development. Growth traits of animals are regulated by many genes which are
responsible for the economic value of the animal (Chen et al 2012). The genes are, therefore, important to consider when designing
breeding programs and identification of such genes is critical for
establishing marker-assisted selection (Li et al 2009). The
current advances in molecular genetics have made possible the identification
of individual genes or candidate genes with substantial effects on the
traits of economic importance. The allelic and genotypic variation at the
candidate genes of interest depicts the differences among breeds on genetic
basis. This variation can be used together with traditional selection
methods to accelerate the rate of change in economically important traits
(Womack 2005). There are many published articles on different genes
associated with meat-related traits in different goat breeds; among these
genes is myostatin (MSTN). Myostatin is a member of the
transforming growth factor- (TGF-) 𝛽 superfamily and it has been shown to
repress muscular growth (Bellinge et al., 2005). Genetic
variation at the MSTN gene has been reported among several goat
breeds (Singh et al., 2014; Tay et al., 2004; Li et
al., 2006) and shown in some breeds to affect body weight at different
stages of growth (Zhang et al., 2013). However, polymorphism of the
genes affecting growth traits in indigenous goats of Tanzania has not been
studied. This study was, therefore, designed to investigate the
polymorphisms of the MSTN
gene and any possible association with growth performance of two SEA strains
and Blended goats.

Materials and methods

Blood sampling and data collection

Blood samples were obtained from Pare (n = 44), Sonjo (n = 40), Blended (n =
31) and Boer goats (n = 29). All the animals were reared at West Kilimanjaro
Research Centre except Boer goats used as a reference breed that were reared
at Ngerengere Government farm. Blood samples were collected from the jugular
vein of the goats using a 10 ml EDTA anticoagulant reagent sterile tube.
Growth records were taken for Pare, Sonjo and Blended goats for four years
from 2010 to 2013. The growth traits evaluated were; birth weight, weaning
weight (at 16 weeks), and yearling weight (at 48 weeks).

DNA Amplification and Sequencing

DNA was isolated using standard commercial kit (Qiagen blood kit,
Chartsworth, USA) according to the manufacturer’s instructions. After
quantification and dilution of the DNA, the region corresponding to the
intron 2 and part of exon 3 of the goat GDF8 gene was amplified by
polymerase chain reaction (PCR) using the following primer pairs;
MSTNstartF (5’-CCCTCCCTTTACTGTCATCC-3’) and MSTNEstopR (5’-
TCA TGA GCA CCC ACA GCG GTC -3’). Each 25 μL PCR reaction contained 50 ng of
sample DNA, 0.4 μM of each primer, 1X PCR buffer (10 mMTris-HCl, pH 8.0, 50
mM KCl), 2.0 mM MgCl2, 0.2 mM of each dNTP and 1 U of Taq DNA
polymerase (Invitrogen). Amplification reactions were carried out in a
thermal cycler (Applied BioSystems), with 5 min denaturation at 94˚C, 34
cycles of denaturation at 94˚C for 45 sec, annealing at 62˚C for 45 sec and
extension at 72˚C for 1 min, and a final extension at 72˚C for 5 min. The
PCR products were stored at 4°C and then detected by gel electrophoresis
using 1% agarose gel. A total of 65 samples were successfully amplified;
Pare (n = 11), Sonjo (n = 5), Blended (n = 20) and Boer (n = 29). The
resulting 700 bp fragments were purified and sequenced with an automated
sequencer (Applied Biosystems 3130).

Statistical analysis

The amplified fragment spanned a region from 1898 to 2276 bases including
parts of intron 2 and exon 3. The resulting sequences were aligned using
Mega V7 and the consensus sequences obtained were compared with the
MSTN GenBank caprine sequences (DQ167575) and single nucleotide
substitutions were identified. The SAS software (SAS Institute, Cary, NC,
USA) was also used to analyse the differences in growth performance between
goat populations. A Linear model was established with effects of population,
sex and year of birth as shown below.

Yijk = μ + Pi +Sj+Tk +e ijkl
where Yijk = Phenotypic observations (Birth weight, weaning weight,
yearling weight), μ = overall mean, Pi = effect of population (Pare,
Sonjo and Boer), Sj = effect of sex (Male and Female), Tk
= effect of year (2010, 2011, 2012 and 2013), eijkl = random error.
It was not possible to assess the association between genotypes of the MSTN
gene and growth performance as no polymorphisms was detected in the gene from
the three populations on which growth data were recorded.

Results and discussion

Polymorphism of the MSTN locus in the goat strains/breed
studied

Parts of intron 2 and exon 3 of goat MSTN gene (AY032689) were
sequenced. The sequenced region from 65 goat samples was 631 bp long.
Results show that the MSTN gene in the goat populations studied is
highly conserved. Only one singleton polymorphic site T298C was detected in
Boer goat population but in the rest of the individuals from other
populations the MSTN gene was monomorphic. Table 1 shows the
genotype and allele frequencies in the different populations. Two alleles, T
and C were detected in Boer goats with frequencies of 0.98 and 0.02,
respectively, and two genotypes TT and TC with frequency of 0.97 and 0.03,
respectively. Allele T was fixed in the Blended, Pare and Sonjo populations.

Table 1.
Allelic and Genotypic frequencies of the alleles and
genotypes, respectively, detected at the MSTN
locus in the four goat populations

Population

Allelic frequency

Genotypic frequency

T

C

TT

TC

Blended

1

0

1

0

Pare

1

0

1

0

Sonjo

1

0

1

0

Boer

0.98

0.02

0.97

0.03

Different studies have detected different number of polymorphic sites within
the same regions of the MSTN gene. Seven polymorphic sites have
been reported in intron 2 in Chinese goats (Li et al., 2006).
Sequencing of all the exons of the MSTN gene revealed three
nucleotide changes in Chinese (Tay et al 2004) and Indian goat
breeds (Singh et al 2014). Digestion of MSTN fragments
with restriction enzymes also found the presence of different genotypes in
Saudi and Egyptian goat breeds (Alakilli et al 2012). However,
Ahad et al (2016), reported no polymorphisms in exon 3 of theMSTN
gene. Inconsistency in genetic polymorphisms of the MSTN gene
has also been observed by many authors in different sheep breeds (Li et
al 2006; Dehnavi et al 2012; Mahrous et al 2014
and Ahad et al 2016). According to Dehnavi et al
(2012), the inconsistency in results from different studies may be
attributed to breed differences, population and sampling size, mating
strategies, geographical position effect, and frequency distribution of
genetic variants. Lack of genetic variability for the MSTN gene
in the Pare, Sonjo and Blended goats in this study may be due to the fact
that the MSTN gene is conserved as these goat populations are
closely related. Also the lack of variation at the MSTN locus
may probably be due to mating strategies used. Animals used in the present
study came from a research station where few sires are used for breeding
thereby increasing the possibility of inbreeding to occur and fixing the few
alleles that would otherwise be variable. Dehnavi et al (2012)
pointed out that the use of few sires for breeding and small effective
population size are the reason for high inbreeding level and consequently
low heterozygosity.

Growth performance of the Small East African and Blended goats

Mean live body weights of Pare, Sonjo and Blended goats at birth, at weaning
and at one year of age are presented in Table 2. Blended goats were the
heaviest at all stages of growth as illustrated in figure 1. There was a
significant difference in growth across years at all stages of growth; kids
born in 2012 showed the best performance. The weight advantage of the
Blended goats compared to the Pare and Sonjo is due to the fact that the
former is a composite breed purposely developed and selected for fast growth
and large mature size. Additionally, Blended goats were developed through
crossbreeding that involved among other breeds, the Boer breed which has
been intensively selected for fast growth and large mature size. Since their
development as a breed, Blended goats have been used in different
interventions by the government and goat producers to increase goat body
size due to their high growth potential. They have been used in breeding
programs by being backcrossed to Small East African goat strains in
different production environments. Fast growth in mammals is determined by
the increases of muscle cell growth and proliferation. Myostatin affects
growth negatively by inhibiting differentiation of myoblasts and the
proliferation of myogenic cells (Thomas et al 2000; Wiener
et al 2009). Presence of different variants of the MSTN
gene was hypothesized to be the cause of differences in growth of goat
populations. Thus, one of the objectives of the present study was to
identify possible genetic variations of the MSTN locus and evaluate
their effect on growth of the studied goats. Lack of variation at the
MSTN locus in Blended, Pare and Sonjo goat populations, despite the
observed differences in their growth performance, suggests that MSTN
locus is not the genetic basis for the observed phenotypic variation. Other
loci related to growth hormone axis have been intensively analysed and
showed to be associated with different growth parameters (Marcel Amills
2014). Analysis of other candidate gene could establish the genetic basis of
the observed variation in growth performance of the studied goats.

Table 2.
Least squares means for weight at different growth stages of
three goat populations

Figure 1. Growth performance of three goat strains at different stages of
growth

Conclusions

From the results of this study, parts of the intron 2 and exon 3 of the
myostatin locus are monomorphic and, hence, highly conserved and, therefore,
cannot be used as a biomarker for marker assisted selection in the studied
goat breeds/strains.

Blended goats are heavier at birth, weaning and one
year of age than the Pare and Sonjo goats.

Further studies targeting the
whole MSTN locus and using larger sample size and animals from
different production environments should be carried ou

Acknowledgements

We acknowledge the financial support from the Tanzania Commission of Science
and Technology (COSTECH) and the National Research Foundation (NRF) of the
Government of South Africa which jointly funded a project titled
“Application of Genomic Tools for Characterization and improved chevon
production from South African and Tanzanian Goats". Additional funding from
COSTECH in the form of PhD scholarship for Athumani Nguluma is greatly
acknowledged. Amplification and Sequencing was done at the College of Animal
Science and Technology, Chongqing Key Laboratory of Forage and Herbivore,
Chongqing Engineering Research Centre for Herbivores Resource Protection and
Utilization, Southwest University, Chongqing, China using their funds. We
thank the farmers who provided the animals for sampling in the villages
where samples were collected and the livestock extension officers for
assisting in field work.

Njombe A P and Msanga Y N 2008
Livestock and Dairy Industry Development in Tanzania, Department of
Livestock Production and Marketing Infrastructure Development. Ministry of
Livestock Development, Tanzania. [http://
www.pagoni.it/index.php?option=com_docman&task=doc_download...20.] site
visited on 16/05/2016.